Publication
SRL without Tears: An ILP Perspective
Kristian Kersting
In: Filip Zelezný; Nada Lavrac (Hrsg.). Inductive Logic Programming, 18th International Conference, Proceedings. International Conference on Inductive Logic Programming (ILP-2008), September 10-12, Prague, Czech Republic, Lecture Notes in Computer Science, Vol. 5194, Springer, 2008.
Abstract
Statistical relational learning addresses one of the central questions of artificial intelligence: the integration of probabilistic reasoning with first order logic representations and machine learning. A rich variety of different formalisms and learning techniques have been developed. This tutorial provides an gentle introduction to and an overview of the state-of-the-art in statistical relational learning. It starts from classical settings for inductive logic programming and shows how they can be extended with probabilistic methods. It touches upon lifted inference and recent developments in nonparametric approaches to statistical relational learning. While doing so, it reviews state-of-the-art statistical relational learning approaches.